Digital channels may be found in various communication and electronic technologies such as telecommunications systems, wireless communication systems, and in the magnetic recording technologies such as the read channel circuitry of some of the more recent and advanced hard disk drives. It is often necessary and desirable to monitor the performance of a digital channel by detecting data errors. The performance of a digital channel may be measured by calculating or estimating a bit-error-rate (BER) or a signal-to-noise ratio (SNR), both of which are related. The monitoring of digital channel performance is necessary and desirable for numerous reasons. For example, the detection of the presence of excessive data errors in the digital channel may be indicative of high levels of undesirable noise, less than optimal circuitry performance, or other problems which, if uncorrected, may harm the overall performance of the associated system or device. By eliminating or reducing any undesirable noise, overall system performance may be improved. Similarly, if the excessive data errors are caused by less than optimal circuitry performance, associated circuitry parameters may be adjusted to improve overall system operation. In some cases, the presence and accumulation of data errors in the digital channel at specified levels or rates may signify an impending system failure.
The capability to accurately and timely monitor digital channel performance by detecting data errors may provide advanced warning of an impending system failure so that appropriate action may be taken to avoid a complete system failure or to minimize the effects of a complete system failure. For example, the presence of data errors at a specified level or rate in the digital channel or read channel of a hard disk drive may indicate an impending disk/head crash. As such, corrective action may be taken to avoid the complete loss of hard disk drive data. The hard disk drive may be backed up and adjustments may be made to prevent a subsequent system failure. Similarly, the SNR may be statistically correlated to overall system failure. For example, the gradual degradation of a hard disk drive media and disk/heads will result in a decrease in the overall SNR of the hard disk drive data channel. The level and amount of change may be statistically correlated to predict an ensuing hard disk drive failure. By predicting this failure in advance, steps can be taken to save the data or to take other steps to prevent the ensuing failure.
Unfortunately, prior techniques used to monitor the performance of a digital channel, such as the read channel of a hard disk drive using advanced signal processing techniques and class IV, partial response (PR4) coding, are complicated and often require complicated circuitry and algorithms. This is especially true in bandwidth confined applications where partial response signaling techniques are used in a highly efficient manner to utilize the limited bandwidth. Prior techniques also often require that a known data pattern be sent through the digital channel and then analyzed for errors. For example, if the read channel of a hard disk drive is the digital channel being monitored, a known data pattern, such as a training field or training data, is first written to the platters of the hard disk drive and then read. The data is monitored as it is being read and compared to the training data to detect errors. Often, a complex algorithm is also provided to analyze the results and to determine the performance of the digital channel or read channel. This is a time consuming and complex solution that requires a significant number of steps and cannot be performed real-time using actual user data because the actual user data is not known and cannot be compared. Furthermore, if the training field is permanently stored on the platters of the hard disk drive for periodic monitoring, the technique suffers the added disadvantage of a reduction in overall storage capacity because of the storage capacity that must be dedicated to the training field. In wireless communication applications, the use of training data increases overall operational costs and reduces overall capacity due the resource allocation involved in transmitting and receiving the training data in place of user data.
Other prior techniques used to monitor the performance of a digital channel, such as the read channel of a hard disk drive, do not require the training field but, instead, require additional circuitry for comparing a data sample with an estimated ideal value. The difference between the data sample and the ideal value is determined and used in a complex algorithm such as the mean-squared-error (MSE) algorithm or the least-mean-square (LMS) algorithm. As such, these techniques require complex circuitry and complex algorithms to perform the necessary operations to monitor the performance of a digital channel. The added circuitry also contributes to overall circuitry die area and increased power consumption.